4. Recurrent Neural Networks (RNN) - Teknowgrade

Artificial Intelligence (AI) 4. Recurrent Neural Networks (RNN)

Artificial Intelligence (AI)

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📘 Module 1: Introduction to Artificial Intelligence

1. What is Artificial Intelligence?

2. History and Evolution of AI

3. Applications of AI in Real Life

4. Types of AI (Narrow, General, Superintelligence)

📘 Module 2: Foundations of AI

1. AI vs Machine Learning vs Deep Learning

2. Components of AI Systems

3. Understanding Algorithms and Models

4. Data in AI – Importance and Types

📘 Module 3: Machine Learning (ML) Basics

1. What is Machine Learning?

2. Supervised vs Unsupervised Learning.

3. Convolutional Neural Networks (CNN)

4. Recurrent Neural Networks (RNN)

📘 Module 5: Natural Language Processing (NLP)

1. What is NLP?

2. Sentiment Analysis

3. Chatbots and Language Translation

4. Real-world NLP Use Cases

📘 Module 6: Computer Vision

1. Basics of Image Processing

2. Object Detection & Recognition

3. Face Recognition Systems

4. Image Classification with Deep Learning

📘 Module 7: Tools & Platforms for AI

1. Python for AI

2. TensorFlow vs PyTorch

3. Using Google Colab

4. Intro to Jupyter Notebooks

📘 Module 8: Ethical and Social Aspects of AI

1. AI Bias and Fairness

2. Job Displacement and Automation

3. AI and Privacy Concerns

4. Responsible AI Guidelines

📘 Module 9: AI in Industry

1. AI in Healthcare

2. AI in Finance

3. AI in Retail and E-Commerce

4. AI in Autonomous Vehicles

📘 Module 10: Capstone Project & Assessment

1. Project Guidelines

2. Build a Simple AI Model (Image or Text-based)

3. Submission & Review

4. Final Quiz / Certification Exam

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